Distribution management for public transit vehicles

ABSTRACT

A method for displaying a visual representation corresponding to a carriage capacity may include obtaining passenger data of passengers onboard a carriage of a multi-carriage vehicle. The method may further include predicting, based at least in part on the first passenger data, a number of passengers who will exit the carriage at a destination. The method may further include determining, based at least in part on the predicting, an available capacity for the carriage and generating a visual representation that corresponds to the available capacity. The method may further include displaying the visual representation at the destination of the multi-carriage vehicle.

BACKGROUND

The present disclosure relates to computer systems, and morespecifically, to systems for handling passenger distribution formulti-carriage vehicles.

Using a multi-carriage vehicle may involve waiting for the vehicle at adestination with multiple passengers and riding onboard the vehicle withmultiple passengers. Passengers may self-distribute according to theirneeds while waiting.

SUMMARY

Some embodiments of the present disclosure can be illustrated as amethod for displaying a visual representation corresponding to acarriage capacity. The method may include obtaining first passenger dataof a first set of passengers. The first set of passengers may be onboarda first carriage of a multi-carriage vehicle. The multi-carriage vehiclemay have a destination. The method may further include predicting, basedat least in part on the first passenger data, a number of the first setof passengers who will exit the first carriage at the destination. Themethod may further include determining, based at least in part on thepredicting, a first available capacity for the first carriage. Themethod may further include generating a first visual representation thatcorresponds to the first available capacity. The method may furtherinclude displaying the first visual representation at the destination.

Some embodiments of the present disclosure can be illustrated as asystem comprising a processor and a memory in communication with theprocessor, the memory containing program instructions that, whenexecuted by the processor, are configured to cause the processor toperform the aforementioned method.

Some embodiments of the present disclosure can be illustrated as acomputer program product, the computer program product comprising acomputer readable storage medium having program instructions embodiedtherewith, the program instructions executable by a computer to causethe computer to perform the aforementioned method.

The above summary is not intended to describe each illustratedembodiment or every implementation of the present disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

The drawings included in the present application are incorporated into,and form part of, the specification. They illustrate embodiments of thepresent disclosure and, along with the description, serve to explain theprinciples of the disclosure. The drawings are only illustrative ofcertain embodiments and do not limit the disclosure.

FIG. 1 depicts an example of a system for facilitating passengerdistribution, in accordance with embodiments of the present disclosure.

FIG. 2 depicts a flowchart of an example method for facilitatingpassenger distribution, in accordance with embodiments of the presentdisclosure.

FIG. 3 depicts the representative major components of a computer systemthat may be used in accordance with embodiments of the presentdisclosure.

FIG. 4 depicts a cloud computing environment according to an embodimentof the present invention.

FIG. 5 depicts abstraction model layers according to an embodiment ofthe present invention.

While the invention is amenable to various modifications and alternativeforms, specifics thereof have been shown by way of example in thedrawings and will be described in detail. It should be understood,however, that the intention is not to limit the invention to theparticular embodiments described. On the contrary, the intention is tocover all modifications, equivalents, and alternatives falling withinthe spirit and scope of the invention.

DETAILED DESCRIPTION

Aspects of the present disclosure relate to computer systems; moreparticular aspects relate to systems for controlling crowd distributionfor multi-carriage vehicles. While the present disclosure is notnecessarily limited to such applications, various aspects of thedisclosure may be appreciated through a discussion of various examplesusing this context.

Multi-carriage vehicles, such as subway trains, trolleys, and trams, maysustain periods of high passenger traffic. During these periods, thelarge number of passengers may contribute to uneven and inefficientdistributions of passengers on vehicle carriages and in the waitingareas for vehicle carriages. Furthermore, during these periods crowdingmay increase the difficulty of passengers finding a carriage thataccommodates the passengers' needs. As a result, inefficient boardingand exiting of carriages may lead to vehicle schedule delays and anunpleasant experience for passengers.

To address these and other problems, embodiments of the presentdisclosure include a method to facilitate passenger distribution forefficient use of multi-carriage vehicles.

Embodiments of the present disclosure include obtaining first passengerdata of a first set of passengers onboard a first carriage of amulti-carriage vehicle that is approaching a destination. The firstpassenger data may include information associated with the first set ofpassengers and/or information associated with the first carriage itself,such as the number of the first set of passengers, a carriage-typedesignation, audio and/or video recordings of the first set ofpassengers, and/or itinerary data of the first set of passengers. Thefirst passenger data may be used to predict the number of passengers whowill exit the first carriage at the destination. Then, the predictednumber may be used to determine an estimated available capacity for thefirst carriage. The determined available capacity may indicate theamount of passenger space that will be available within the firstcarriage after the predicted number of first passengers exits the firstcarriage at the destination. A first visual representation thatcorresponds with the determined available capacity may be generated anddisplayed at the destination before the first carriage arrives at thedestination.

This display of the first visual representation at the destination maypermit a second set of passengers at the destination to self-distributeabout a waiting area according to their needs. For example, a visualrepresentation may include a carriage-type designation, such as awheelchair-accessible designation, that would permit a passenger havingsuch a need to self-distribute near a stopping location for thewheelchair-accessible carriage. Additionally, the display of the firstvisual representation may permit the second set of passengers toself-distribute to avoid a crowded transition between first passengersexiting a carriage at the destination and second passengers boarding thecarriage at the destination.

For example, a visual representation showing that an arriving carriageis at full capacity may encourage passenger(s) awaiting themulti-carriage vehicle (e.g., train) to self-distribute near a stoppingposition of an arriving carriage that is empty. Accordingly, embodimentsof the present disclosure may permit efficient boarding and exiting ofmulti-carriage vehicles. As a result, embodiments of the presentdisclosure may improve the experience of traveling on multi-carriagevehicles in addition to improving the overall operating efficiency ofmulti-carriage vehicles. Additionally, since the visual representationmay be perceived without the user needing specific technology, such as asmart phone, embodiments of the present disclosure may provideinformation in a way that is easily accessible to all passengers at thedestination.

Additionally, some embodiments of the present disclosure includemonitoring a set of second passengers at a destination to obtain secondpassenger data. The second passenger data may be used to estimate anumber of passengers who will board an arriving carriage, and the visualrepresentation may be updated in real-time to include the estimation.This updating of the visual representation may further enhanceself-distribution efficiency by permitting passengers at the destinationto adjust their position based on the movements of other passengers,thereby reducing bottlenecking that occurs when, for example, a largenumber of passengers try to board a carriage with insufficient capacity.

It is to be understood that the aforementioned advantages are exampleadvantages and should not be construed as limiting. Embodiments of thepresent disclosure can contain all, some, or none of the aforementionedadvantages while remaining within the spirit and scope of the presentdisclosure.

Turning to the figures, FIG. 1 depicts an example operating environment100 in which illustrative examples of the present disclosure may beimplemented. Operating environment 100 may be a destination, such as asubway station, train depot, or a tram terminal, where a multi-carriagevehicle 190 may arrive for passenger boarding and exiting.Multi-carriage vehicle 190 may be a vehicle, such as a trolley, train,or tram, having multiple passenger carriages 150, 151, 152.

Each carriage 150, 151, 152 may be equipped with one or more cameras 145and/or one or more sensors 135. The cameras 145 may be configured toobtain images and/or audio recordings of a first set of passengers 120distributed within each carriage 150, 151, 152. The sensors 135 mayinclude a variety of types, such as seat occupant sensors, carriageweight sensors, wireless device detectors, and motion sensors. Thecameras 145 and sensors 135 may be configured to obtain data about thefirst set of passengers 120 onboard each carriage 150, 151, 152. Suchdata may include information such as a total number of passengers on thecarriage, a number of seated passengers, a density of passengerspositioned in a particular portion of the carriage (e.g., near the doorswhere they would exit at the next stop), and/or a direction of motion ofone or more passengers. Furthermore, the cameras 145 and the sensors 135may be connected to one or more processors that may analyze and/orprocess data obtained from the cameras and the sensors. Furthermore, theprocessors may receive other data, such as passenger itinerary data,from the passengers themselves (e.g., from a wireless communication linkwith their phone) or from a remote server (e.g., a server that maintainsbooking information for the multi-carriage vehicle).

For example, in some embodiments, a carriage may be equipped with awireless device detector that may provide an approximate number ofwireless devices present on the carriage. That number may be transmittedto a processor to aid in determining how many passengers are onboard thecarriage. In some embodiments, camera image data may be transmitted to aprocessor for image analysis to aid in predicting a number of passengersonboard the carriage who are likely to exit at the destination. Forexample, the processor may analyze a set of images to determine a numberof people in an area that indicates they may be preparing to get off thetrain (e.g., near the door) and/or to determine a number of peoplemoving towards the doors (e.g., by analysis of video).

Additionally, each carriage may be designated to offer one or morefeatures, such as wireless internet access, wheelchair accessibility, orquiet space (e.g., where talking or otherwise making noise are stronglydiscouraged).

A second set of passengers 110 may be distributed about a waitingplatform 180 within the operating environment 100. Furthermore, a visualrepresentation 130, 131, 132 may be viewable to the second set ofpassengers 110. The visual representation 130, 131, 132 may includeinformation that corresponds to a specific carriage of themulti-carriage vehicle. For example, the visual representation mayinclude an indicator 140 (e.g., a wireless communication icon) thatshows a feature that is available on the corresponding carriage (e.g.,available wireless internet access). The visual representation may alsoinclude information such as a number of first passengers onboard acarriage, an available capacity of a carriage, and/or a predicteddeparture capacity of a carriage (i.e., a predicted capacity of thecarriage after passengers have had an opportunity to exit and board thecarriage at the destination). Each carriage 150, 151, 152 may have adistinct, corresponding visual representation 130, 131, 132 that may bedisplayed approximately adjacent to an approximate stopping position170, 171, 172 of the carriage at the destination 100.

For example, in FIG. 1, a first carriage 152 has an approximate stoppingposition 172 at the destination 100. Adjacent to stopping position 172,visual representation 132 may include information corresponding to thefirst carriage 152, such as which features are available on the firstcarriage 152 and/or a predicted departure capacity of the first carriage152. This configuration permits the second set of passengers (e.g., thepassengers waiting to board the multi-carriage vehicle) to easily matcheach carriage with its corresponding carriage data and self-distributeaccordingly.

The visual representations 130, 131, 132 may take one or more forms,including without limitation a set of colors or patterns, a set ofimages, a set of alphanumeric characters, and/or a set of audio sounds.Additionally, the visual representations may be displayed in a varietyof ways. For example, in some embodiments, a visual representation mayinclude a projection onto a surface within the operating environment(e.g., a projection onto a surface of the waiting platform 180). In someembodiments, a visual representation may include a set of electronicdisplay screens within the operating environment. In some embodiments, avisual representation may include an illuminated section of a structurewithin the operating environment, such as an illuminated section of afloor, wall, and/or ceiling. In some embodiments, a visualrepresentation may include a projection onto a carriage or anillumination of a portion of a carriage of a multi-carriage vehicle. Insome embodiments, the visual representation may include illuminating(e.g., by projection, embedded lights, etc.) a set of doors that blockoff access to the tracks when the train is not in the station, such asmay be found in airports or subways.

In some embodiments, there may be multiple sets of visualrepresentations. Each set may correspond to a different multi-carriagevehicle that is scheduled to arrive at the destination. For example, afirst set of visual representations (e.g., the set nearest the tracks)may correspond to the first (e.g., next) arriving train. A second set ofvisual representations (e.g., a set further away from the tracks orlocated in another area) may correspond to a second arriving train. Thesecond arriving train may be scheduled to arrive after the firstarriving train has departed from the destination. Accordingly,passengers who are not boarding the first arriving train maynevertheless begin self-distributing for the second arriving train.

In some embodiments, the operating environment may include a set ofsensors 165 and a set of cameras 155 configured to obtain secondpassenger data about the second set of passengers at the waitingplatform. The sensors 165 may include a variety of types, such aswireless device detectors and/or motion sensors. The second passengerdata may include information pertaining to the passengers waiting at theplatform, such as a total number of second passengers and/or a directionof motion of one or more second passengers. Furthermore, the cameras 155and the sensors 165 may be connected to one or more processors that mayanalyze and/or process data obtained from the cameras and the sensors.Using the second passenger data, the processor may update the visualrepresentations in real-time based on a current passenger distributionof the second passengers (e.g., based on where passengers are currentlyqueued for boarding the train). For example, even if an approachingcarriage is completely empty, if the number of passengers lined up toget on that carriage exceeds the capacity of the carriage, the visualrepresentation may be updated to encourage additional passengers to movetowards another carriage.

In some embodiments, the operating environment 100 may further include aprocessor 160. The processor 160 may communicate with an array ofdevices, such as one or more external storage and/or processing devices,such as one or more servers. The processor may communicate with sensors135, cameras 145, and/or equipment (not shown) used to display thevisual representation 130, 131, 132. In some embodiments, the processor160 may communicate with one or more processors on the multi-carriagevehicle. In some embodiments, the processor 160 may be located remotelylocated from the operating environment.

FIG. 2 depicts an embodiment of an example method 200 for facilitatingpassenger distribution, in accordance with embodiments of the presentdisclosure. The method 200 may be performed (e.g., automatically) by acomputer system (e.g., computer system 301 shown in FIG. 3). The method200 may begin at step 210, where first passenger data of passengersonboard a carriage of the multi-carriage vehicle may be obtained. Thefirst passenger data may be obtained from one or more sensors or camerasconnected to the multi-carriage vehicle. The first passenger data mayalso be obtained from one or more storage and/or processing devices incommunication with one or more sensors or cameras connected to themulti-carriage vehicle. In some embodiments, step 210 may includeobtaining historical data regarding the multi-carriage vehicle from oneor more storage and/or processing devices. For example, historical datamay include information such as previously acquired sensor or cameradata, statistical data regarding passenger activity at a particular timeof day, a predetermined maximum passenger capacity for each carriage,and/or data regarding a feature available on the carriage.

Step 220 includes predicting a number of passengers who will exit thecarriage at a travel destination of the carriage. Step 220 may includeanalyzing the first passenger data. For example, step 220 may includedetermining a number of passengers who transition from a seated positionto a standing position as the carriage approaches a destination. Thistransition may be determined by analyzing a set of seat occupant sensors(e.g. by analyzing a quantity of sensors that transitioned fromindicating that a seat was occupied to indicating that a seat becameunoccupied). In another example, images of passengers may show a numberof standing passengers who move toward a carriage doorway as thecarriage approaches a destination. Using the number of passengers at (ormoving toward) the carriage doorway, a computer system may predict howmany passengers are exiting at the next stop. In some embodiments, thecomputer system may use the sensor data and the historical data topredict the number of passengers exiting the carriage. Other sensors,such as sensors placed near the doors that can detect the number ofpassengers at the doors or the change in the number of passengers at thedoors, may similarly be used to predict the number of passengers exitingthe carriage.

Step 230 includes determining an available passenger capacity onboardthe carriage. For example, determining an available capacity may includesubtracting a number of passengers onboard the carriage from apredetermined maximum passenger capacity for the carriage, and from theresult, adding the predicted number of passengers who will exit thecarriage.

Step 240 includes generating a visual representation to be displayed atthe destination. For example, step 240 may include a set of computercommands to associate a set of variables with carriage-specific data(e.g., FEATURE=“Quiet Space Carriage”, AVAILABLE CAPACITY=20) that willbe included in the visual representation. Step 240 may also includetransmitting data that is to be displayed at the destination.

In some embodiments, step 240 includes generating one or more visualindicators for each carriage. The visual indicators may indicate thefeatures of the carriage (e.g., amenities such as internet access), aswell as the predicted available capacity for new passengers (e.g.,passengers waiting at the next stop) based on the current capacity andthe number of passengers expected to exit the carriage. In someembodiments, the amenities features may be predicted amenities availableto passengers waiting to get on the carriage. For example, if a carriagehas two wheelchair accessible seating areas, but both are unlikely to beavailable at the next stop, the visual indicator displayed may not showthe carriage as being wheelchair accessible, or it may show that thecarriage is wheelchair accessible, but that it is at capacity.

The visual indicators may be generated using one or more thresholds. Forexample, the system may be configured to display three levels ofavailable capacity using color LEDs: Red for carriages with >80% of thetotal capacity occupied (e.g., high occupancy), yellow for carriageswith between 40% and 80% of the total capacity occupied (e.g., moderateoccupancy), and green for carriages with under 40% of the total capacityoccupied (e.g., low occupancy). The system may compare the predictedcapacity for each carriage to the thresholds to determine which colorcorresponds to each carriage, and then displays the colors at thedestination (e.g., the next stop).

In some embodiments, the thresholds may be based on historical dataand/or current capacity of the multi-carriage vehicle as a whole. Forexample, during peak hours where the train is generally near full, thethreshold may be changed to 90 and 75 percent capacity to reflect thefact that each carriage is likely to be more full than usual, and anycarriage with less than 75% of the total capacity occupied is,relatively speaking, an open carriage. Similarly, during low occupancyhours, the thresholds may be adjusted downward (e.g., to 50% and 25%).

Step 250 includes displaying the visual representation at thedestination. During step 250, data corresponding to the carriage is madevisible to a second set of passengers at the destination. Step 250 mayinclude actions such as illuminating a set of display screens and/orprojecting a set of patterns or images. Step 250 may also includeemitting a set of audio sounds at the destination. Additionally, step250 may occur before the multi-carriage vehicle arrives at thedestination to allow passengers to self-distribute in a more efficientmanner.

Step 260 includes obtaining second passenger data of a second set ofpassengers at the destination. The second passenger data may be obtainedfrom one or more sensors or cameras at the destination. The secondpassenger data may also be obtained from one or more storage and/orprocessing devices in communication with one or more sensors or camerasat the destination. For example, the second passenger data may includeitinerary data for passengers at the platform. In some embodiments, step260 may include obtaining historical data regarding passenger transitactivity at the destination from one or more storage and/or processingdevices.

For example, step 260 may include using a set of cameras and a set ofweight sensors arranged at a destination to monitor in real-time how thesecond set of passengers are self-distributing about a waiting platformat the destination. Additionally, historical data may be obtained, suchas whether the destination is typically crowded at a particular time ofday.

Step 270 includes estimating a number of passengers who will board acarriage at the destination. Step 270 may also include predicting adeparture capacity (i.e., a capacity of the carriage after firstpassengers and second passengers have had an opportunity to exit andboard the carriage at the destination). Estimating a number ofpassengers who will board the carriage may include analyzing the secondpassenger data. For example, a processor may utilize machine learning toestimate, based on a passenger's movement patterns and stationarylocations at a waiting platform, whether the passenger is likely toboard an approaching carriage.

Step 280 includes updating the visual representation based on theestimated number of passengers who will board the carriage at thedestination. For example, a set of second passengers at a destinationmay observe a visual representation regarding an approachingthree-carriage vehicle having carriage 1, carriage 2, and carriage 3.The visual representation indicates that carriage 1 has the highestavailable capacity, followed, in order of descending capacity, bycarriage 2 and then carriage 3. Since the visual representation showsthat carriage 1 has the highest available capacity, a large number ofthe second passengers self-distribute adjacent to the stopping positionof carriage 1. The changed distribution of second passengers is detectedby a set of sensors and cameras at the destination. A processor analyzesthe sensor and camera data, estimates that a large number of secondpassengers will board carriage 1, and updates the display. The updateddisplay shows that the predicted departure capacity of carriage 1 is atfull capacity and that the predicted departure capacity of carriage 2 isat medium capacity. When some of the second passengers observe thepredicted departure capacities, they reposition themselves adjacent tothe stopping position of carriage 2, with intent to board a carriagewith a lower predicted departure capacity. As the second passengerscontinue to self-distribute, the visual representations are continuouslyupdated, such that when the multi-carriage vehicle arrives, the secondpassengers may be self-distributed according to their needs and/orpreferences.

FIG. 3 depicts the representative major components of an exemplaryComputer System 301 (e.g., for predicting and displaying carriageavailability) that may be used in accordance with embodiments of thepresent disclosure. The particular components depicted are presented forthe purpose of example only and are not necessarily the only suchvariations. The Computer System 301 may comprise a Processor 310, Memory320, an Input/Output Interface (also referred to herein as I/O or I/OInterface) 330, and a Main Bus 340. The Main Bus 340 may providecommunication pathways for the other components of the Computer System301. In some embodiments, the Main Bus 340 may connect to othercomponents such as a specialized digital signal processor (notdepicted).

The Processor 310 of the Computer System 301 may be comprised of one ormore CPUs 312. The Processor 310 may additionally be comprised of one ormore memory buffers or caches (not depicted) that provide temporarystorage of instructions and data for the CPU 312. The CPU 312 mayperform instructions on input provided from the caches or from theMemory 320 and output the result to caches or the Memory 320. The CPU312 may be comprised of one or more circuits configured to perform oneor methods consistent with embodiments of the present disclosure. Insome embodiments, the Computer System 301 may contain multipleProcessors 310 typical of a relatively large system. In otherembodiments, however, the Computer System 301 may be a single processorwith a singular CPU 312.

The Memory 320 of the Computer System 301 may be comprised of a MemoryController 322 and one or more memory modules for temporarily orpermanently storing data (not depicted). In some embodiments, the Memory320 may comprise a random-access semiconductor memory, storage device,or storage medium (either volatile or non-volatile) for storing data andprograms. The Memory Controller 322 may communicate with the Processor310, facilitating storage and retrieval of information in the memorymodules. The Memory Controller 322 may communicate with the I/OInterface 330, facilitating storage and retrieval of input or output inthe memory modules. In some embodiments, the memory modules may be dualin-line memory modules.

The I/O Interface 330 may comprise an I/O Bus 350, a Terminal Interface352, a Storage Interface 354, an I/O Device Interface 356, and a NetworkInterface 358. The I/O Interface 330 may connect the Main Bus 340 to theI/O Bus 350. The I/O Interface 330 may direct instructions and data fromthe Processor 310 and Memory 320 to the various interfaces of the I/OBus 350. The I/O Interface 330 may also direct instructions and datafrom the various interfaces of the I/O Bus 350 to the Processor 310 andMemory 320. The various interfaces may comprise the Terminal Interface352, the Storage Interface 354, the I/O Device Interface 356, and theNetwork Interface 358. In some embodiments, the various interfaces maycomprise a subset of the aforementioned interfaces (e.g., an embeddedcomputer system in an industrial application may not include theTerminal Interface 352 and the Storage Interface 354).

Logic modules throughout the Computer System 301—including but notlimited to the Memory 320, the Processor 310, and the I/O Interface330—may communicate failures and changes to one or more components to ahypervisor or operating system (not depicted). The hypervisor or theoperating system may allocate the various resources available in theComputer System 301 and track the location of data in Memory 320 and ofprocesses assigned to various CPUs 312. In embodiments that combine orrearrange elements, aspects of the logic modules' capabilities may becombined or redistributed. These variations would be apparent to oneskilled in the art.

It is understood in advance that although this disclosure includes adetailed description on cloud computing, implementation of the teachingsrecited herein are not limited to a cloud computing environment. Rather,embodiments of the present invention are capable of being implemented inconjunction with any other type of computing environment now known orlater developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g. networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based e-mail).The consumer does not manage or control the underlying cloudinfrastructure including network, servers, operating systems, storage,or even individual application capabilities, with the possible exceptionof limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring now to FIG. 4, illustrative cloud computing environment 50 isdepicted. As shown, cloud computing environment 50 comprises one or morecloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Nodes 10 maycommunicate with one another. They may be grouped (not shown) physicallyor virtually, in one or more networks, such as Private, Community,Public, or Hybrid clouds as described hereinabove, or a combinationthereof. This allows cloud computing environment 50 to offerinfrastructure, platforms and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 4 are intended to be illustrative only and that computing nodes10 and cloud computing environment 50 can communicate with any type ofcomputerized device over any type of network and/or network addressableconnection (e.g., using a web browser).

Referring now to FIG. 5, a set of functional abstraction layers providedby cloud computing environment 50 (FIG. 4) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 5 are intended to be illustrative only and embodiments of theinvention are not limited thereto. As depicted, the following layers andcorresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 61; RISC(Reduced Instruction Set Computer) architecture based servers 62;servers 63; blade servers 64; storage devices 65; and networks andnetworking components 66. In some embodiments, software componentsinclude network application server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers71; virtual storage 72; virtual networks 73, including virtual privatenetworks; virtual applications and operating systems 74; and virtualclients 75.

In one example, management layer 80 may provide the functions describedbelow. Resource provisioning 81 provides dynamic procurement ofcomputing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 82provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 83 provides access to the cloud computing environment forconsumers and system administrators. Service level management 84provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 85 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 90 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 91; software development and lifecycle management 92; virtualclassroom education delivery 93; data analytics processing 94;transaction processing 95; and capacity prediction logic 96.

As discussed in more detail herein, it is contemplated that some or allof the operations of some of the embodiments of methods described hereinmay be performed in alternative orders or may not be performed at all;furthermore, multiple operations may occur at the same time or as aninternal part of a larger process.

The present invention may be a system, a method, and/or a computerprogram product. The computer program product may include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers, and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the variousembodiments. As used herein, the singular forms “a,” “an,” and “the” areintended to include the plural forms as well, unless the context clearlyindicates otherwise. It will be further understood that the terms“includes” and/or “including,” when used in this specification, specifythe presence of the stated features, integers, steps, operations,elements, and/or components, but do not preclude the presence oraddition of one or more other features, integers, steps, operations,elements, components, and/or groups thereof. In the previous detaileddescription of example embodiments of the various embodiments, referencewas made to the accompanying drawings (where like numbers represent likeelements), which form a part hereof, and in which is shown by way ofillustration specific example embodiments in which the variousembodiments may be practiced. These embodiments were described insufficient detail to enable those skilled in the art to practice theembodiments, but other embodiments may be used and logical, mechanical,electrical, and other changes may be made without departing from thescope of the various embodiments. In the previous description, numerousspecific details were set forth to provide a thorough understanding thevarious embodiments. But, the various embodiments may be practicedwithout these specific details. In other instances, well-known circuits,structures, and techniques have not been shown in detail in order not toobscure embodiments.

Different instances of the word “embodiment” as used within thisspecification do not necessarily refer to the same embodiment, but theymay. Any data and data structures illustrated or described herein areexamples only, and in other embodiments, different amounts of data,types of data, fields, numbers and types of fields, field names, numbersand types of rows, records, entries, or organizations of data may beused. In addition, any data may be combined with logic, so that aseparate data structure may not be necessary. The previous detaileddescription is, therefore, not to be taken in a limiting sense.

The descriptions of the various embodiments of the present disclosurehave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the describedembodiments. The terminology used herein was chosen to explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the embodimentsdisclosed herein.

What is claimed is:
 1. A method comprising: obtaining first passenger data of a first set of passengers onboard a first carriage of a multi-carriage vehicle, the multi-carriage vehicle having a destination; predicting, based at least in part on the first passenger data, a number of the first set of passengers who will exit the first carriage at the destination; determining, based at least in part on the predicting, a first available capacity for the first carriage; generating a first visual representation that corresponds to the first available capacity; displaying, at a first time, the first visual representation at the destination, the first visual representation visible on a surface of a first ground region at the destination; obtaining, at a second time subsequent to the first time, by one or more devices at the destination, second passenger data of a second set of passengers at the destination, the second set of passengers not onboard the multi-carriage vehicle, the second passenger data comprising a first position of the second set of passengers; updating, at a third time subsequent to the second time, the first visual representation based on the second passenger data; obtaining, at a fourth time subsequent to the third time, by the one or more devices at the destination, third passenger data of the second set of passengers, the third passenger data comprising a second position of the second set of passengers, the second position different from the first position; and updating, at a fifth time subsequent to the fourth time, the first visual representation based on the third passenger data, wherein the one or more devices are selected from the group consisting of cameras and sensors.
 2. The method of claim 1, wherein the first visual representation is visible to the second set of passengers.
 3. The method of claim 1, wherein the updating at the fifth time occurs before the multi-carriage vehicle arrives at the destination.
 4. The method of claim 1, further comprising transmitting the first available capacity over a network to a receiving device.
 5. The method of claim 1, wherein the first visual representation is visible adjacent to a stopping position of the first carriage at the destination.
 6. The method of claim 2, further comprising estimating a number of the second set of passengers who will board the multi-carriage vehicle at the destination.
 7. The method of claim 6, wherein the updating at the third time comprises adjusting the first visual representation based on the estimating.
 8. The method of claim 1, wherein the first visual representation further includes an indicator that describes a feature available on the first carriage.
 9. A system comprising: a memory; and a processor communicatively coupled to the memory, wherein the processor is configured to perform a method comprising: obtaining first passenger data of a first set of passengers onboard a first carriage of a multi-carriage vehicle, the multi-carriage vehicle having a destination; predicting, based at least in part on the first passenger data, a number of the first set of passengers who will exit the first carriage at the destination; determining, based at least in part on the predicting, a first available capacity for the first carriage; generating a first visual representation that corresponds to the first available capacity; displaying, at a first time, the first visual representation at the destination, the first visual representation visible on a surface of a first ground region at the destination; obtaining, at a second time subsequent to the first time, by one or more devices at the destination, second passenger data of a second set of passengers at the destination, the second set of passengers not onboard the multi-carriage vehicle, the second passenger data comprising a first position of the second set of passengers; updating, at a third time subsequent to the second time, the first visual representation based on the second passenger data; obtaining, at a fourth time subsequent to the third time, by the one or more devices at the destination, third passenger data of the second set of passengers, the third passenger data comprising a second position of the second set of passengers, the second position different from the first position; and updating, at a fifth time subsequent to the fourth time, the first visual representation based on the third passenger data, wherein the one or more devices are selected from the group consisting of cameras and sensors.
 10. The method of claim 1, wherein the first visual representation further comprises a predicted departure capacity corresponding to the first carriage; and wherein the updating at the fifth time comprises updating the predicted departure capacity for the first carriage.
 11. The system of claim 9, wherein the first visual representation is visible to the second set of passengers.
 12. The system of claim 11, wherein the method performed by the processor further comprises estimating a number of the second set of passengers who will board the multi-carriage vehicle at the destination.
 13. The system of claim 12, wherein the updating at the third time comprises adjusting the first visual representation based on the estimating.
 14. The system of claim 9, wherein the updating at the fifth time occurs before the multi-carriage vehicle arrives at the destination.
 15. The system of claim 9, wherein the method performed by the processor further comprises transmitting the first available capacity over a network to a receiving device.
 16. The system of claim 9, wherein the first visual representation is visible adjacent to a stopping position of the first carriage at the destination.
 17. A computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform a method comprising: obtaining first passenger data of a first set of passengers onboard a first carriage of a multi-carriage vehicle, the multi-carriage vehicle having a destination; predicting, based at least in part on the first passenger data, a number of the first set of passengers who will exit the first carriage at the destination; determining, based at least in part on the predicting, a first available capacity for the first carriage; generating a first visual representation that corresponds to the first available capacity; displaying, at a first time, the first visual representation at the destination, the first visual representation visible on a surface of a first ground region at the destination; obtaining, at a second time subsequent to the first time, by one or more devices at the destination, second passenger data of a second set of passengers at the destination, the second set of passengers not onboard the multi-carriage vehicle, the second passenger data comprising a first position of the second set of passengers; updating, at a third time subsequent to the second time, the first visual representation based on the second passenger data; obtaining, at a fourth time subsequent to the third time, by the one or more devices at the destination, third passenger data of the second set of passengers, the third passenger data comprising a second position of the second set of passengers, the second position different from the first position; and updating, at a fifth time subsequent to the fourth time, the first visual representation based on the third passenger data, wherein the one or more devices are selected from the group consisting of cameras and sensors.
 18. The computer program product of claim 17, wherein the first visual representation is visible to the second set of passengers.
 19. The computer program product of claim 18, wherein the method performed by the processor further comprises estimating a number of the second set of passengers who will board the multi-carriage vehicle at the destination.
 20. The computer program product of claim 19, wherein the updating at the third time comprises adjusting the first visual representation based on the estimating. 